PyTorch Developer Podcast By cover art

PyTorch Developer Podcast

By: Edward Yang Team PyTorch
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  • Summary

  • The PyTorch Developer Podcast is a place for the PyTorch dev team to do bite sized (10-20 min) topics about all sorts of internal development topics in PyTorch.
    2021 - PyTorch Developer Podcast
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Episodes
  • TORCH_TRACE and tlparse

    TORCH_TRACE and tlparse
    Apr 29 2024
    TORCH_TRACE and tlparse are a structured log and log parser for PyTorch 2. It gives useful information about what code was compiled and what the intermediate build products look like.
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    15 mins
  • Higher order operators

    Higher order operators
    Apr 21 2024
    Higher order operators are a special form of operators in torch.ops which have relaxed input argument requirements: in particular, they can accept any form of argument, including Python callables. Their name is based off of their most common use case, which is to represent higher order functions like control flow operators. However, they are also used to implement other variants of basic operators and can also be used to smuggle in Python data that is quite unusual. They are implemented using a Python dispatcher.
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    17 mins
  • Inductor - Post-grad FX passes

    Inductor - Post-grad FX passes
    Apr 12 2024
    The post-grad FX passes in Inductor run after AOTAutograd has functionalized and normalized the input program into separate forward/backward graphs. As such, they generally can assume that the graph in question is functionalized, except for some mutations to inputs at the end of the graph. At the end of post-grad passes, there are special passes that reintroduce mutation into the graph before going into the rest of Inductor lowering which is generally aware of passes. The post-grad FX passes are varied but are typically domain specific passes making local changes to specific parts of the graph.
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    24 mins
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